Towards a Semantically-Enabled Control Strategy for Building Simulations: Integration of Semantic Technologies and Model Predictive Control
State-of-the-art building simulation control methods incorporate physical constraints into their mathematical models, but omit implicit constraints associated with policies of operation and dependency relationships among rules representing those constraints. To overcome these shortcomings, there is a recent trend in enabling the control strategies with inference-based rule checking capabilities. One solution is to exploit semantic web technologies in building simulation control. Such approaches provide the tools for semantic modeling of domains, and the ability to deduce new information based on the models through use of Description Logic (DL). In a step toward enabling this capability, this paper presents a cross-disciplinary data-driven control strategy for building energy management simulation that integrates semantic modeling and formal rule checking mechanisms into a Model Predictive Control (MPC) formulation. The results show that MPC provides superior levels of performance when initial conditions and inputs are derived from inference-based rules.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1434875
- Report Number(s):
- PNNL-SA-126011
- Resource Relation:
- Conference: Proceedings of the 15th IBPSA Conference (IBPSA 2017), August 7-9, 2017, San Francisco, California, 965-974
- Country of Publication:
- United States
- Language:
- English
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